浅析规模化畜禽集中养殖环境污染现状及防治对策——以安居区玉丰镇为例

通过实地调查取样分析,结果表明:玉丰镇鸡头寺村和金龟村规模化畜禽集中养殖实际出栏量是土地环境容量1.3倍,土壤中含锌、铜、锰、砷量分别为163.05mg/kg、156.00mg/kg、101.13mg/kg和9.19mg/kg,已造成土壤污染,农田灌溉用水化学需氧量超标准限值503%,地下水和大气受到一定程度的污染。     

成都市餐厨垃圾产量分析预测及监管体系建设研究

整理汇总了成都市中心城区及郊县餐厨垃圾产生和收运现状,对其产量作出预测;在此基础上提出适合成都市自身情况的餐厨垃圾监管体系构建设想。     

重庆市道路交通空气监测现状及控制对策

分析重庆市道路交通空气质量自动监测站的各项参数监测数据的变化趋势,并对机动车尾气对大气环境的影响进行了分析与评估。同时结合一些先进的预防、控制和处理汽车尾气污染的方法,提出了一些意见和建议来防止机动车尾气污染进一步蔓延。     

四川省能源-社会经济-环境复合系统能流分析

能源是现代社会发展的重要基础,其在社会经济发展中占有不可替代的地位。以四川省统计年鉴及相关数据资料为基础,参考美国能流图绘制了四川省2010年的能流图,并对四川省2005~2010年间的能源输入、输出、消耗,以及相应的污染物排放进行了分析,分析发现:近年来能源消费总量增长迅速,年均增长率达10.8%,能源对外依存度较高,尤其是石油。能源消耗结构有待进一步优化,传统化石能源所占比重偏高,2010年达77.18%。同时构建了能源-社会经济-环境复合系统能流分析指标,分析了2005~2010年四川省能源、经济、环境两两子系统及三者系统之间的协调度,结果显示:四川省能源-经济-环境系统协调度不断上升,2010年三者综合协调度0.97238。最后根据能流分析、污染物排放水平、协调度分析等结果,提出了四川省能源发展战略、能流的优化管理、节能减排等对策建议。     

山西省城乡统筹发展效率的DEA分析

基于2009年山西省11个地级市城乡统筹发展的面板数据,运用数据包络分析（DEA）评价了各区域的城乡统筹发展效率,对其空间差异变化特征与规律进行了分析。结果表明,山西省城乡统筹发展效率总体上呈＂中部较高,普遍分化＂的分布特征,并存在两大＂DEA有效＂集群。自改革开放以来,山西省逐渐形成了中、东、西三大经济地带,即中部盆地区、东部山地区和西部高原丘陵区。规模效率是当前制约山西省城乡统筹发展综合效率的主要方面。全省普遍存在投入冗余现象,可通过优化环境、产业结构高级化、突出特色产业、提升产业技术、提高劳动力素质和城市化水平等途径来提高区域的城乡统筹发展效率。各区域之间城乡统筹发展效率的空间差异显著;对2009年山西省11个地级市进行相对效率分析,得出相对有效值为1的城市居多,北部朔州市和南端运城市相对效率差异明显,最后提出了相关政策建议。     

苏州国际旅游节城市旅游效应研究与思考

现代节庆活动发展迅速,有效塑造了城市旅游形象,促进了城市旅游业的发展。以苏州国际旅游节为例,对历届苏州国际旅游节进行了初步梳理和分析,利用相关数据,对其产生的旅游经济效应、社会文化效应和环境效应进行了综合评价,认为苏州国际旅游节成功塑造了苏州的城市形象,刺激了苏州旅游业发展,有利于苏州旅游资源的有效整合。当前苏州国际旅游节在运营模式、主题创新和当地居民参与度等方面还存在一些问题,对此进行了思考并提出改进建议,以期更好地发挥苏州国际旅游节的整体旅游效应。     

石羊河流域生态脆弱性评价研究

综合分析自然条件和人类活动对区域生态系统的两方面影响,建立了生态脆弱性评价指标体系,运用层次分析法和综合指数法计算了石羊河流域9县（区）的生态脆弱度分值。根据计算结果,将石羊河流域划分为4级生态脆弱区,分别为极强度脆弱区、强度脆弱区、中度脆弱区和轻度脆弱区。在此基础上,对各脆弱区提出生态治理对策,为今后流域开展生态经济功能区划提供依据。     

基于排队论的城市垃圾箱最佳间距研究

针对城市垃圾箱最佳间距的研究不够精细的现状,本文通过建立排队论模型得到了可供不同城市参考的城市垃圾箱最佳间距参数表。通过对部分城市街道的垃圾箱摆放间距情况进行实地调查,运用层次分析法将影响垃圾箱间距分布的多重因素转化为单因素;建立了基于指数分布的数学模型,利用排队论分析单因素状态下的垃圾箱间距分布,得到了求解城市垃圾箱最佳间距的一般方法。     

Bioaccessibility of polychlorinated biphenyls in workplace dust and its implication for risk assessment

Human exposure to bioaccessible PCBs via indoor dust is limited around the world. In the present study, the workplace dust sample from commercial office, hospital, secondary school, shopping mall, electronic factory and manufacturing plant were collected from Hong Kong for PCBs analyses. Total PCBs concentrations ranged from 46.8 to 249 ng g⁻¹, with a median of 107 ng g⁻¹. Manufacturing plant showed the highest concentration among all of sampling sites. PCB 77 was found as the dominant congeners. The bioaccessibility of PCBs in small intestinal juice ranging from 8.3% to 26.0% was significantly higher than that in gastric condition, ranging from 4.8% to 12.4%. In addition, significant negative correlations (p < 0.05) were observed between K_OW and bioaccessibility for all workplace dust samples. Risk assessment indicated that the averaged daily dose of dioxin-like PCBs via non-dietary intake of workplace dust, considering the bioaccessibility of PCBs, were much lower than the TDI of dioxins (2.3 pg WHO-TEQ kg bw⁻¹ d⁻¹) established by Joint FAO/WHO Expert Committee on Food Additives.     

Phosphine in paddy fields and the effects of environmental factors

Ambient levels of phosphine (PH₃) in the air, phosphine emission fluxes from paddy fields and rice plants, and the distribution of matrix-bound phosphine (MBP) in paddy soils were investigated throughout the growing stages of rice. The relationships between MBP and environmental factors were analyzed to identify the principal factors determining the distribution of MBP. The phosphine ambient levels ranged from 2.368 ± 0.6060 ng m⁻³ to 24.83 ± 6.529 ng m⁻³ and averaged 14.25 ± 4.547 ng m⁻³. The highest phosphine emission flux was 22.54 ± 3.897 ng (m² h)⁻¹, the lowest flux was 7.64 ± 4.83 ng (m² h)⁻¹, and the average flux was 14.17 ± 4.977 ng (m² h)⁻¹. Rice plants transport a significant portion of the phosphine emitted from the paddy fields. The highest contribution rate of rice plants to the phosphine emission fluxes reached 73.73% and the average contribution was 43.00%. The average MBP content of 111.6 ng kg⁻¹fluctuated significantly in different stages of rice growth and initially increased then decreased with increasing depth. The peak MBP content in each growth stage occurred approximately 10 cm under the surface of paddy soils. Pearson correlation analyses and stepwise multiple regression analysis showed that soil temperature (Ts), acid phosphatase (ACP) and total phosphorus (TP) were the principal environmental factors, with correlative rankings of Ts > ACP > TP.